According to DeepLearning.AI, AI engineers now drive build loops, make product calls, lead org alignment, and own outcomes to maximize impact.

According to DeepLearningAI, a new context tool helps agents reduce memory bloat and API spend for production retrieval, as reported by The Batch.

According to DeepLearningAI, Andrew Ng outlines four skills—build loops, product decisions, broad comms, high ownership—to level up AI engineering.

According to DeepLearning.AI, coding agents shift dev work to specs, architecture, and review; Andrew Ng outlines 5 core skills to steer agent workflows.

According to DeepLearning.AI, Zai’s GLM-5.3-Flash hits 320B params, runs China-made hardware, and leads GDPval AA v2 at $0.09 per task.

According to DeepLearningAI, top teams curb agent autonomy with human review, iterative plans, and verification to cut costs and failures.

According to DeepLearning.AI, a free course with Google Cloud teaches a self-critiquing UI design agent for brand-consistent images.

According to DeepLearning.AI, Xiaohongshu’s Self-GC uses a planner LLM to keep, fold, or prune tokens, retaining key details 84.85% vs 54.55% baselines.

According to DeepLearningAI, agents need core software engineering—full stack, data, architecture, security, and ops—to ship reliable AI apps.

According to DeepLearningAI, Andrew Ng urges mastering full-stack, data, architecture, security, and ops to ship reliable AI apps.

According to DeepLearningAI, a free course teaches agents to learn from traces and build code knowledge graphs in partnership with Oracle.

According to DeepLearningAI on X, Andrew Ng outlines six AI engineering skills from LLM foundations to ops for building reliable AI apps.

According to DeepLearningAI, Andrew Ng outlines LLM foundations, data grounding, agents, evals, ops, and ML basics as core AI engineering skills.

According to DeepLearning.AI, the team seeks an AI-native dev to build agentic workflows and automations in Mountain View, enabling scalable marketing ops.

According to DeepLearningAI on X, Omar Wael completed the Machine Learning Specialization, sharing reflections that may inspire upskilling paths.

According to DeepLearningAI, a free course shows how to split subagents, use cheaper models, and run coding agents fully local across workflows.

According to DeepLearningAI, a free course with QodoAI teaches risk triage, context-driven reviews, and building an LLM review agent.

According to AndrewYNg, DeepLearning.AI launched a short course with Cerebras on wafer-scale fast inference for real-time LLM apps and agentic workflows.

According to DeepLearning.AI on X, a 7‑day Voice AI Builder Challenge saw 500+ iterations and 38 submissions, naming three top winners after human review.

According to DeepLearningAI, 38 submissions and 500 plus iterations produced top Voice AI agents that place phone calls when stuck.